Create main.py

main.py

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+# Import libraries
+import whisper
+import os
+import gradio as gr
+from groq import Groq
+from gtts import gTTS
+import traceback
+from google.colab import userdata
+
+# Step 1: Load Whisper Model for Transcription
+try:
+    model = whisper.load_model("base")
+except Exception as e:
+    print("Error loading Whisper model:", e)
+    model = None
+
+# Step 2: Initialize Groq Client
+try:
+    client = Groq(api_key = os.getenv("MY_API_KEY"))
+except Exception as e:
+    print("Error initializing Groq client:", e)
+    client = None
+
+# Function to get response from Groq API using LLaMA model
+def get_response_from_groq(user_input):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": user_input}],
+            model="llama3-8b-8192",
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        print("Error getting response from Groq API:", e)
+        return "Sorry, I couldn't generate a response at this time."
+
+# Step 3: Function to convert text to speech using gTTS
+def text_to_speech(text):
+    try:
+        tts = gTTS(text)
+        tts.save("response.mp3")
+        return "response.mp3"
+    except Exception as e:
+        print("Error converting text to speech:", e)
+        return None
+
+# Step 4: Define the Chatbot Function for Gradio
+def chatbot(audio_input):
+    try:
+        if model is None:
+            return "Whisper model not loaded.", "Unable to transcribe.", None
+        
+        # Transcribe audio input using Whisper
+        transcription = model.transcribe(audio_input)["text"]
+        
+        # Get response from Groq API using LLaMA model
+        response = get_response_from_groq(transcription)
+        
+        # Convert response to speech
+        speech_file = text_to_speech(response)
+        
+        return transcription, response, speech_file
+    except Exception as e:
+        print("Error in chatbot function:", e)
+        traceback.print_exc()
+        return "Error occurred during processing.", "Please try again.", None
+
+# Step 5: Create Gradio Interface
+try:
+    gr.Interface(
+        fn=chatbot,
+        inputs=gr.Audio(type="filepath"),
+        outputs=["text", "text", "audio"],
+        live=True
+    ).launch()
+except Exception as e:
+    print("Error launching Gradio interface:", e)